Book Image

Data Smart

By : John W. Foreman
Book Image

Data Smart

By: John W. Foreman

Overview of this book

Data Science gets thrown around in the press like it's magic. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, math and the magic, behind big data.
Table of Contents (18 chapters)
Free Chapter
1
Cover
2
Credits
3
About the Author
4
About the Technical Editors
5
Acknowledgments
18
End User License Agreement

There and Back Again: A Gephi Tale

Now that you've gone through the entire clustering process, I'd like to show you that same process in Gephi. In Figure 5.20, you examined a laid out export of the r-Neighborhood graph into Gephi, which I return to in this section.

This next step is going to make you envious, but here it goes. In Excel you had to solve for the optimal graph modularity using divisive clustering. In Gephi, there's a Modularity button. You'll find it on the right side of the window in the Network Overview section of the Statistics tab.

When you press the Modularity button, a settings window opens. You needn't use edge weights since you exported an adjacency matrix (see Figure 5.41 for the Gephi modularity settings window).

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Figure 5.41 Gephi modularity settings

Press OK. The modularity optimization will run using an approximation algorithm that's blindingly fast. A report is then displayed with a total modularity score of 0.549 as well as...